Computer Science student at the University of Toronto · Machine Learning Engineer · Software Engineer
I'm completing a Computer Science Specialist and Mathematics Minor at the University of Toronto. I’m interested in machine learning, reasoning models, and the powerful systems that make ML useful in practice.
Applied Machine Learning Engineer Intern · Cerebras Systems
Toronto · May 2025 – August 2026
Toronto · January – April 2025
Computer Vision Researcher · Computational Vision and Imaging Lab, York University
Toronto · May – August 2024 · Lassonde Undergraduate Research Award
- Undergraduate Researcher, Autonomous Vision Group, Koç University KUIS AI Research Centre · June – September 2023.
- Machine Learning Engineer Intern, TAZI AI Systems · May – August 2023.
Through Students Developing Software (SDS) (2023–2024), I contributed to open-source tools used in University of Toronto courses:
- MarkUs · Contributed to a Ruby on Rails, React, and PostgreSQL grading platform used by 5,000+ students. My pull requests
- PythonTA · Contributed to Python static-analysis tools used in courses by 5,000+ students annually. My pull requests
- MemoryViz · Helped turn a JavaScript/Node.js prototype into a maintainable learning tool used by thousands. My pull requests
I was a Lead Tutorial Teaching Assistant for CSC236 for two terms and am currently the Machine Learning Projects Director at UTMIST (since September 2024).
Areas: Machine learning, LLM reasoning and post-training, computer vision, distributed systems, software engineering
Languages: Python, C++, C, SQL, Shell, Java, JavaScript, Haskell
ML: PyTorch, FlexAttention, tensor parallelism, distributed training, vLLM, verl, Hugging Face Transformers, Inspect, scikit-learn
Backend and systems: FastAPI, gRPC, RabbitMQ, PostgreSQL, Linux, Docker, Slurm/HPC, GPU programming, Git, CI/CD
Stats are based on public GitHub activity. Language proportions reflect code size across public repositories, not time spent coding.